Senior Data Scientist(Python is a must)

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

• Serve as an analytics expert in designing, developing and implementing best in analytic solutions
• Create and deliver powerful insights from data through better visualization and storyboarding
• Collaborate with internal and external partners to fully understand business requirements and desired business outcomes
• Demonstrate execution proficiency in handing multiple medium-to-large analytics projects in a team environment that includes the rest of the Data Science team
• Draft detailed scope for assigned projects, addressing suggested methodology and analytics plan
• Execute on the analytics plan with appropriate data mining and analytical techniques
• Perform quality assurance of data and deliverables for work performed by other Data Scientists and self
• Ensure all project documentation is up to date and all projects are reviewed per analytics plan
• Ensure project delivery within timelines and budget requirements
• Build on team’s analytical skills and business knowledge
• Enhance existing analytics techniques by promoting new methodologies and best practices in the Data Science field
• Provide subject matter expertise and quality assurance of complex data-driven analytic projects

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.

Basic Qualifications: Minimum of 6-8 years of analytics expertise in applying statistical solutions to business problems Preferred Qualifications: Experience working in one or more of the Card Payments markets around the globe Post-graduate degree (Masters or PhD) in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent Good understanding of the Payments and Banking Industry including aspects such as consumer credit, consumer debit, prepaid, small business, commercial, co-branded and merchant Good knowledge of data, market intelligence, business intelligence, and AI-driven tools and technologies Experience planning, organizing, and managing multiple large projects with diverse cross-functional teams Demonstrated ability to incorporate new techniques to solve business problems Demonstrated resource planning and delivery skills Experience in distributed computing environments , big data platforms (Hadoop, Elasticsearch, etc.) as well as common database systems and value stores (SQL, Hive, HBase, etc.) Ability to write scratch MapReduce jobs and fluency with Spark frameworks Familiarity with both common computing environments (e.g. Linux, Shell Scripting) and commonly-used IDE’s (Jupyter Notebooks) proficiency in SAS technologies and techniques Strong programming ability in different programming languages such as Python, R, Scala, Java, Matlab, C++, and SQL Experience in drafting solution architecture frameworks that rely on API’s and micro-services Familiarity with common data modeling approaches, and ability to work with various datatypes including JSON, XML, etc. Ability to build data pipelines (e.g. ETL, data preparation, data aggregation and analysis) using tools such as NiFi, Sqoop, Ab Initio familiarity with data lineage processes and schema management tools. Proficient in some or all of the following techniques Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Markov Chain, Monte Carlo, Gibbs Sampling, Evolutionary Algorithms (e.g. Genetic Algorithms, Genetic Programming), Support Vector Machines, Neural Networks, etc. Expert knowledge of advanced data mining and statistical modeling techniques, including Predictive modeling (e.g., binomial and multinomial regression, ANOVA) Classification techniques (e.g., Clustering, Principal Component Analysis, factor analysis) Decision Tree techniques (e.g., CART, CHAID) Deliver results within committed scope, timeline and budget Very strong people/project management skills and experience.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.